1. Field of the Invention
The present invention relates to image composition apparatuses and methods; more particularly, the present invention relates to image composition apparatuses and methods that generate a composite image by combining portions of different source images.
2. Descriptions of the Related Art
Digital image capture devices/units (e.g. digital camera mobile devices) have been evolved fast with better functionality and performances and are capable to capture multiple images in a relatively short time. User may perform burst mode shooting to capture a series of images either automatically or manually. Normally, such series of images are captured with the same scene and object(s). Once such series of images are obtained, the series of images can be further processed to generate composite images with particular effect or composition.
Image composition is about generating a pleasant composite image with desired effect by combining different parts of two or more images. Although lots of techniques and applications for composing images have been developed, most of them deal with images taken from different views and hence focus on accurately segmenting regions for composition and color blending at the boundaries of the composed regions. In the meantime, for those conventional image composition techniques, regions to be composed usually can be easily identified.
In reality, images usually contain incomplete or noisy information about the desired regions so that the regions to be composed are often poorly identified. That is, the initially obtained regions may have significant parts of unnecessary or undesired pixels but miss great parts of desired pixels. In addition, the regions may have significant overlapping with counterparts in other images. The imprecision of the identified regions to be composed are not considered by conventional image composition technique. Although this problem may be a proper task for the well-known graph-cut framework to work on, graph-cut may not be a practical solution for media production, as its memory-intensive nature prevents it from dealing with high resolution images on moderate computing platform. Besides, such optimization approaches are often not intuitive for further tuning and evaluation.
Consequently, there is still an urgent need for an efficient image composition technique that can deal with the regions that can only be poorly identified.